Dynamic analysis system

ABSTRACT

A dynamic analysis system includes a hardware processor and an output device. The hardware processor obtains a cycle of temporal change in a feature amount relevant to a function to be diagnosed from each of dynamic images obtained by imaging of a dynamic state of a living body with radiation. The hardware processor further adjusts the obtained cycle, thereby generating a plurality of cycle-adjusted data having cycles of the temporal change in the feature amount being equal to one another. The hardware processor further generates difference information at each phase in the plurality of cycle-adjusted data. The output device outputs the difference information.

BACKGROUND 1. Technological Field

This invention relates to a dynamic analysis system.

2. Description of the Related Art

When dynamic images obtained by imaging of a cyclic dynamic state of asubject are compared with one another for interpretation, there may bedifference in cycle of the dynamic state between the dynamic images,which leads to inappropriate comparison and evaluation.

There is described, for example, in WO 2014/054379 A1, a technique ofsynchronizing cyclic changes of a base moving image and a referencemoving image to be compared with the base moving image at a particularphase in each cycle of the reference moving image and displaying thesetwo moving images.

However, even if cycles of dynamic images are matched with one anotherand these dynamic images are displayed simultaneously as described in WO2014/054379 A1, it is difficult to intuitively note their difference.

SUMMARY

Objects of the invention include readily understanding differencebetween dynamic images that are compared with one another.

In order to achieve at least one of the objects, according to an aspectof the invention, there is provided a dynamic analysis system including:a hardware processor that: obtains a cycle of temporal change in afeature amount relevant to a function to be diagnosed from each ofdynamic images obtained by imaging of a dynamic state of a living bodywith radiation; adjusts the obtained cycle, thereby generating aplurality of cycle-adjusted data having cycles of the temporal change inthe feature amount being equal to one another; and generates differenceinformation at each phase in the plurality of cycle-adjusted data; andan output device that outputs the difference information.

According to another aspect of the invention, there is provided adynamic analysis system including: a hardware processor that: obtains acycle of temporal change in a feature amount relevant to a function tobe diagnosed from each of analysis result images of respective dynamicimages obtained by imaging of a dynamic state of a living body withradiation, wherein the analysis result images show results of dynamicanalysis of the respective dynamic images on a pixel basis or a blockbasis, the block being constituted of a plurality of pixels; adjusts theobtained cycle, thereby generating a plurality of cycle-adjusted datahaving cycles of the temporal change in the feature amount being equalto one another; and generates difference information at each phase inthe plurality of cycle-adjusted data; and an output device that outputsthe difference information.

BRIEF DESCRIPTION OF THE DRAWINGS

The advantages and features provided by one or more embodiments of theinvention will become more fully understood from the detaileddescription given hereinbelow and the appended drawings which are givenby way of illustration only, and thus are not intended as a definitionof the limits of the invention, wherein:

FIG. 1 shows the overall configuration of a dynamic analysis systemaccording to embodiments of the invention;

FIG. 2 is a flowchart of an imaging control process that is performed bya controller of an imaging console shown in FIG. 1;

FIG. 3 is a flowchart of a difference display process A that isperformed by a controller of a diagnostic console shown in FIG. 1according to a first embodiment;

FIG. 4 is a diagram to explain cycle adjustment;

FIG. 5 shows a difference image (moving image) displayed in Step S16 inFIG. 3;

FIG. 6 is a flowchart of a difference display process B that isperformed by the controller of the diagnostic console shown in FIG. 1according to a second embodiment;

FIG. 7 shows a difference graph displayed in Step S25 in FIG. 6;

FIG. 8 is a flowchart of a difference display process C that isperformed by the controller of the diagnostic console shown in FIG. 1according to a third embodiment; and

FIG. 9 shows a difference image (moving image) displayed in Step S36 inFIG. 8.

DETAILED DESCRIPTION OF EMBODIMENTS

Hereinafter, one or more embodiments of the invention will be describedin detail with reference to the drawings. However, the scope of theinvention is not limited to the disclosed embodiments.

First Embodiment

[Configuration of Dynamic Analysis System 100]

First, the configuration of a first embodiment is described.

FIG. 1 shows the overall configuration of a dynamic analysis system 100according to the first embodiment.

As shown in FIG. 1, the dynamic analysis system 100 includes: an imager1; an imaging console 2 connected with the imager 1 via a communicationcable or the like; and a diagnostic console 3 connected with the imagingconsole 2 via a communication network NT, such as a LAN (Local AreaNetwork). These apparatuses of the dynamic analysis system 100 are inconformity with DICOM (Digital Image and Communications in Medicine)standard and communicate with one another in conformity with DICOM.

[Configuration of Imager 1]

The imager 1 is an imager that images a cyclic dynamic state. Examplesof the cyclic dynamic state include: change in shape of the lung fieldsby expansion and contraction of the lung fields with breathing; andpulsation of the heart. Dynamic imaging (kinetic imaging) is performedby repeatedly emitting pulsed radiation, such as pulsed X-rays, to asubject at predetermined time intervals (pulse emission) or continuouslyemitting radiation without a break to a subject at a low dose rate(continuous emission), thereby obtaining a plurality of images showingthe dynamic state of the subject. A series of images obtained by dynamicimaging is called a dynamic image. Images constituting a dynamic imageare called frame images. In the embodiments described hereinafter,dynamic imaging of a chest is performed by pulse emission as an example.

A radiation source 11 is disposed to face a radiation detector 13 with asubject M (examinee) interposed therebetween, and emits radiation(X-rays) to the subject M under the control of a radiation emissioncontroller 12.

The radiation emission controller 12 is connected with the imagingconsole 2, and controls the radiation source 11 on the basis ofradiation emission conditions input from the imaging console 2 so as toperform imaging with radiation (radiation imaging). The radiationemission conditions input from the imaging console 2 include a pulserate, a pulse width, a pulse interval, the number of frames (frameimages) to be taken by one imaging, a value of current of an X-ray tube,a value of voltage of the X-ray tube, and a type of added filter. Thepulse rate is the number of times radiation is emitted per second, andmatches the frame rate described below. The pulse width is duration ofradiation emission per time. The pulse interval is a period of time fromthe start of one radiation emission to the start of the next radiationemission, and matches the frame interval described below.

The radiation detector 13 is constituted of a semiconductor imagesensor, such as an FPD. The FPD is constituted of detection elements(pixels) arranged at predetermined points on a substrate, such as aglass substrate, in a matrix. The detection elements detect radiation(intensity of radiation) that has been emitted from the radiation source11 and passed through at least the subject M, convert the detectedradiation into electric signals, and accumulate the electric signalstherein. The pixels are provided with switches, such as TFTs (Thin FilmTransistors). There are an indirect conversion type FPD that convertsX-rays into electric signals with photoelectric conversion element(s)via scintillator(s) and a direct conversion type FPD that directlyconverts X-rays into electric signals. Either of them can be used.

The radiation detector 13 is disposed to face the radiation source 11with the subject M interposed therebetween.

A reading controller 14 is connected with the imaging console 2. Thereading controller 14 controls the switches of the pixels of theradiation detector 13 on the basis of image reading conditions inputfrom the imaging console 2 to switch the pixels to read the electricsignals accumulated in the pixels, thereby reading the electric signalsaccumulated in the radiation detector 13 and obtaining image data. Thisimage data is a frame image(s). The reading controller 14 outputs theobtained frame images to the imaging console 2. The image readingconditions include a frame rate, a frame interval, a pixel size, and animage size (matrix size). The frame rate is the number of frame imagesto be obtained per second, and matches the pulse rate described above.The frame interval is a period of time from the start of one frame imageobtaining action to the start of the next frame image obtaining action,and matches the pulse interval described above.

The radiation emission controller 12 and the reading controller 14 areconnected to one another, and exchange sync signals so as to synchronizeradiation emission actions with image reading actions.

[Configuration of Imaging Console 2]

The imaging console 2 outputs the radiation emission conditions and theimage reading conditions to the imager 1 so as to control the radiationimaging and the radiation image reading actions performed by the imager1, and also displays the dynamic image obtained by the imager 1 so thata radiographer, such as a radiologist, can check if positioning has noproblem, and also can determine if the dynamic image is suitable fordiagnosis.

The imaging console 2 includes, as shown in FIG. 1, a controller 21, astorage 22, an operation unit 23, a display 24 and a communication unit25. These units or the like are connected to one another via a bus 26.

The controller 21 includes a CPU (Central Processing Unit) and a RAM(Random Access Memory). The CPU of the controller 21 reads a systemprogram and various process programs stored in the storage 22 inresponse to operations with the operation unit 23, opens the readprograms in the RAM, and performs various processes, such as thebelow-described imaging control process, in accordance with the openedprograms, thereby performing concentrated control of actions of theunits or the like of the imaging console 2 and the radiation emissionactions and the reading actions of the imager 1.

The storage 22 is constituted of a nonvolatile semiconductor memory, ahard disk or the like. The storage 22 stores therein various programs tobe executed by the controller 21, parameters necessary to performprocesses of the programs, data, such as process results, and so forth.For example, the storage 22 stores therein a program for the imagingcontrol process shown in FIG. 2. The storage 22 also stores therein theradiation emission conditions and the image reading conditions forrespective imaging sites to be examined (here, the chest). The programsare stored in the form of computer readable program code, and thecontroller 21 acts in accordance with the program code.

The operation unit 23 includes: a keyboard including cursor keys, numberinput keys and various function keys; and a pointing device, such as amouse, and outputs, to the controller 21, command signals input by keyoperations on the keyboard or by mouse operations. The operation unit 23may have a touchscreen on the display screen of the display 24. In thiscase, the operation unit 23 outputs command signals input via thetouchscreen to the controller 21.

The display 24 is constituted of a monitor, such as an LCD (LiquidCrystal Display) or a CRT (Cathode Ray Tube), and displays thereon inputcommands from the operation unit 23, data and so forth in accordancewith commands of display signals input from the controller 21.

The communication unit 25 includes a LAN adapter, a modem and a TA(Terminal Adapter), and controls data exchange with apparatusesconnected to the communication network NT.

[Configuration of Diagnostic Console 3]

The diagnostic control 3 is an apparatus that obtains the dynamic imagefrom the imaging console 2, and displays the obtained dynamic imageand/or the analysis result of the dynamic image to help a doctor(s) makea diagnosis.

The diagnostic console 3 includes, as shown in FIG. 1, a controller 31,a storage 32, an operation unit 33, a display 34 and a communicationunit 35. These units or the like are connected to one another via a bus36.

The controller 31 includes a CPU (hardware processor) and a RAM. The CPUof the controller 31 reads a system program and various process programsstored in the storage 32 in response to operations with the operationunit 33, opens the read programs in the RAM, and performs variousprocesses, such as the below-described difference display process A, inaccordance with the opened programs, thereby performing concentratedcontrol of actions of the units or the like of the diagnostic console 3.

The storage 32 is constituted of a nonvolatile semiconductor memory, ahard disk or the like. The storage 32 stores therein various programs,including a program for the difference display process A, to be executedby the controller 31, parameters necessary to perform processes of theprograms, data, such as process results, and so forth. The programs arestored in the form of computer readable program code, and the controller31 acts in accordance with the program code.

The storage 32 stores therein the dynamic image, which has been taken inthe past, correlated with patient information (e.g. patient ID, name,height, weight, age, sex, etc.) and examination information (e.g.examination ID, examination date, site to be examined (here, the chest),type of function to be diagnosed (e.g. ventilation, perfusion,diaphragm, etc.), etc.).

The operation unit 33 includes: a keyboard including cursor keys, numberinput keys and various function keys; and a pointing device, such as amouse, and outputs, to the controller 31, command signals input by keyoperations on the keyboard or by mouse operations. The operation unit 33may have a touchscreen on the display screen of the display 34. In thiscase, the operation unit 33 outputs command signals input via thetouchscreen to the controller 31.

The display 34 is constituted of a monitor, such as an LCD or a CRT, andperforms various types of display in accordance with commands of displaysignals input from the controller 31.

The communication unit 35 includes a LAN adapter, a modem and a TA, andcontrols data exchange with apparatuses connected to the communicationnetwork NT.

[Actions of Dynamic Analysis System 100]

Next, actions of the dynamic analysis system 100 according to thisembodiment are described.

[Actions of Imager 1 and Imaging Console 2]

First, imaging actions that are performed by the imager 1 and theimaging console 2 are described.

FIG. 2 shows the imaging control process that is performed by thecontroller 21 of the imaging console 2. The imaging control process isperformed by the controller 21 in cooperation with the program stored inthe storage 22.

First, a radiographer operates the operation unit 23 of the imagingconsole 2 so as to input patient information on an examinee (subject M),and examination information on an examination to be performed on theexaminee (Step S1).

Next, the controller 21 reads radiation emission conditions from thestorage 22 so as to set them in the radiation emission controller 12,and also reads image reading conditions from the storage 22 so as to setthem in the reading controller 14 (Step S2).

Next, the controller 21 waits for a radiation emission command to beinput by the radiographer operating the operation unit 23 (Step S3).Here, the radiographer places the subject M between the radiation source11 and the radiation detector 13 and performs positioning. Further, theradiographer instructs the examinee (subject M) about how to breathe,for example, instructs the examinee to relax and encourages him/her todo quiet breathing. If the type of the function to be diagnosed isventilation, the radiographer may instruct the examinee to do quietbreathing, whereas if the type of the function to be diagnosed isperfusion, the radiographer may instruct the examinee to stop breathing.When preparations for imaging are complete, the radiographer operatesthe operation unit 23 so as to input the radiation emission command.

When receiving the radiation emission command input through theoperation unit 23 (Step S3; YES), the controller 21 outputs an imagingstart command to the radiation emission controller 12 and the readingcontroller 14 to start dynamic imaging (Step S4). That is, the radiationsource 11 emits radiation at pulse intervals set in the radiationemission controller 12, and accordingly the radiation detector 13obtains (generates) a series of frame images.

When imaging for a predetermined number of frame images finishes, thecontroller 21 outputs an imaging end command to the radiation emissioncontroller 12 and the reading controller 14 to stop the imaging actions.The number of frame images to be taken covers at least one breathingcycle.

The frame images obtained by imaging are successively input to theimaging console 2 and stored in the storage 22, the frame images beingcorrelated with respective numbers indicating what number in the imagingorder the respective frame images have been taken (frame numbers) (StepS5), and also displayed on the display 24 (Step S6). The radiographerchecks the positioning or the like with the displayed dynamic image, anddetermines whether the dynamic image obtained by dynamic imaging issuitable for diagnosis (Imaging OK) or re-imaging is necessary (ImagingNG). Then, the radiographer operates the operation unit 23 so as toinput the determination result.

When the determination result “Imaging OK” is input by the radiographerperforming a predetermined operation with the operation unit 23 (StepS7; YES), the controller 21 attaches, to the respective frame images ofthe dynamic image obtained by dynamic imaging (e.g. writes, in theheader region of the image data in DICOM), information such as an ID toidentify the dynamic image, the patient information, the examinationinformation, the radiation emission conditions, the image readingconditions, and the respective numbers indicating what number in theimaging order the respective frame images have been taken (framenumbers), and sends the same to the diagnostic console 3 through thecommunication unit 25 (Step S8), and then ends the imaging controlprocess. On the other hand, when the determination result “Imaging NG”is input by the radiographer performing a predetermined operation withthe operation unit 23 (Step S7; NO), the controller 21 deletes the frameimages of the dynamic image from the storage 22 (Step S9), and then endsthe imaging control process. In this case, re-imaging is necessary.

[Actions of Diagnostic Console 3]

Next, actions of the diagnostic console 3 are described.

In the diagnostic console 3, when receiving a series of frame images ofa dynamic image based on which ventilation or perfusion is diagnosedfrom the imaging console 2 through the communication unit 35, thecontroller 31 performs the difference display process A shown in FIG. 3in cooperation with the program stored in the storage 32.

Hereinafter, the flow of the difference display process A is describedwith reference to FIG. 3.

First, a past dynamic image to be compared with the received dynamicimage is selected (Step S10).

In Step S10, for example, a list of past dynamic images of the subject Mstored in the storage 32 is displayed on the display 34, and from thedisplayed dynamic images, a dynamic image desired by a user is selectedthrough the operation unit 33, or from the past dynamic images of thesubject M stored in the storage 32, a dynamic image having the latestexamination date is automatically selected by the controller 31. Notethat the received dynamic image is referred to as a current dynamicimage, and the dynamic image to be compared with the current dynamicimage is referred to as a past dynamic image.

Next, the controller 31 performs warping on the current dynamic imageand the past dynamic image so as to match the shapes of regions of lungfields (hereinafter “lung field region shapes”) (Step S11).

For example, in Step S11, first, the contours of the lung field regionsare detected from each frame image of the current dynamic image and eachframe image of the past dynamic image. For example, for each frameimage, a threshold value is obtained from a histogram of signal values(density values) of pixels by discriminant analysis, and regions havinghigher signal values than the threshold value are extracted as lungfield region candidates. Then, edge detection is performed on around theborder of each extracted lung field region candidate, and, in smallregions around the border, points where the edge is the maximum areextracted along the border. Thus, the borders of the lung field regionscan be extracted. Next, one frame image is selected from all the frameimages of the current dynamic image and the past dynamic image as areference image, and warping is performed such that the lung fieldregion shapes in the other frame images match the lung field regionshapes in the reference image. The reference image may be the firstframe image of the current dynamic image or the past dynamic image, ormay be a frame image at the maximal expiratory level or the maximalinspiratory level. Alternatively, an image of the lung field regionshapes may be prepared beforehand as a reference, and the lung fieldregion shapes in both dynamic images may be made to match the lung fieldregion shapes serving as the reference. This makes the lung field regionshapes always the same when dynamic images are compared with oneanother, and accordingly a user can compare and evaluate the dynamicimages under the same environment.

Next, the controller 31 calculates the feature amount (here, signalvalue(s) of an ROI) relevant to the function to be diagnosed from eachof the current dynamic image and the past dynamic image, and obtainscycles of temporal change in the calculated feature amount (Step S12).

As to the ventilation function by respiration, when the lung fieldsexpand by inspiration, the density of the lung fields decreases, so thatthe X-ray transmission amount increases, and the signal values (densityvalues) of the lung field regions in a dynamic image increases. On theother hand, when the lung fields contract by expiration, the density ofthe lung fields increases, so that the X-ray transmission amountdecreases, and the signal values of the lung field regions in a dynamicimage decreases. Hence, if the function to be diagnosed is ventilation,temporal change in signal value of a dynamic image can be used astemporal change in the feature amount relevant to the ventilationfunction. Further, when blood flows into the lung fields by respiration,the X-ray transmission amount at the parts where the blood flowsdecreases, and the signal values of the parts in a dynamic imagedecreases. Hence, if the function to be diagnosed is perfusion, temporalchange in signal value of a dynamic image can be used as temporal changein the feature amount relevant to the perfusion function.

If the function to be diagnosed is, for example, ventilation, first,low-pass filtering in the time direction is performed on the lung fieldregions in both the past dynamic image and the current dynamic image.More specifically, for each pixel of each dynamic image, temporal changein signal value is obtained and filtered with a time-direction low-passfilter (e.g. a cutoff frequency of 0.80 Hz). This can remove thehigh-frequency component due to perfusion or the like and obtain thesignal component due to ventilation.

Next, in each frame image of each of the two low-pass filtered dynamicimages, an ROI (region of interest) is set. It is preferable that theROI be set at a location where the feature relevant to the function tobe diagnosed appears most clearly. If the function to be diagnosed isventilation, it is preferable that the ROI be set in the lung fieldregions excluding the heart and backbones. The ROI may be setautomatically by image processing or may be set in response to a useroperation through the operation unit 33 (i.e. manually).

Next, for each of the current dynamic image and the past dynamic image,a representative value (e.g. the mean, the median, etc.) of the signalvalues of the pixels of the ROI in each frame image is calculated, and agraph of the waveform (called a waveform graph) showing temporal changein signal value (representative value) is generated by plotting thecalculated representative values in chronological order (in order of theframe images).

Then, cycles of temporal change in signal value of the current dynamicimage and the past dynamic image are obtained from the respectivewaveform graphs generated. Time from a local maximum point (or localminimum point) to the next local maximum point (or local minimum point)of the waveform graph(s) can be calculated as a cycle.

If the function to be diagnosed is, for example, perfusion, first,high-pass filtering in the time direction is performed on the lung fieldregions in both the past dynamic image and the current dynamic image.More specifically, for each pixel of each dynamic image, temporal changein signal value is obtained and filtered with a time-direction high-passfilter (e.g. a cutoff frequency of 0.80 Hz). The temporal change insignal value may be filtered with a time-direction bandpass filter (e.g.a lower-limit cutoff frequency of 0.8 Hz and an upper-limit cutofffrequency of 2.4 Hz). This can remove the low-frequency component due toventilation or the like and obtain the signal component due toperfusion.

Next, in each frame image of each of the two filtered dynamic images, anROI (region of interest) is set. It is preferable that the ROI be set ata location where the feature relevant to the function to be diagnosedappears most clearly. If the function to be diagnosed is perfusion, itis preferable that the ROI be set in the heart region. The ROI may beset automatically by image processing or may be set in response to auser operation through the operation unit 33 (i.e. manually).

Next, for each of the current dynamic image and the past dynamic image,a representative value (e.g. the mean, the median, etc.) of the signalvalues of the pixels of the ROI in each frame image is calculated, and agraph of the waveform (waveform graph) showing temporal change in signalvalue (representative value) is generated by plotting the calculatedrepresentative values in chronological order (in the order of the frameimages).

Then, cycles of temporal change in signal value in the current dynamicimage and the past dynamic image are obtained from the respectivewaveform graphs generated.

Next, the controller 31 performs cycle adjustment to match the cyclescalculated from the current dynamic image with the cycles calculatedfrom the past dynamic image, thereby generating two cycle-adjusted data(Step S13).

In Step S13, if the cycles obtained from the current dynamic image andthe cycles obtained from the past dynamic image are different from oneanother as shown in FIG. 4, cycle adjustment is performed, so that twocycle-adjusted data, the cycles of which are equal to one another, aregenerated. In this embodiment, cycle-adjusted data are the dynamicimages, the cycles of which have been matched with one another (here,the current dynamic image and the past dynamic image, the cycles ofwhich have been matched with one another).

For example, first, cycles (cycles of temporal change in signal value;the same applies hereinafter) of the dynamic images after adjustment aredetermined. As the cycles after adjustment, shorter cycles that one ofthe dynamic images has may be used so that cycles of the other dynamicimage are adjusted thereto, or longer cycles that one of the dynamicimages has may be used so that cycles of the other dynamic image areadjusted thereto. Alternatively, cycles of both of the dynamic imagesmay be adjusted to a predetermined cycle(s).

Next, in order to match the cycles of the respective dynamic images withthe cycles after adjustment, for each cycle of each dynamic image, thenumber of frame images to be added or deleted is determined. If thenumber of frame images to be added or deleted is 0, the cycles of such adynamic image are not changed. In each cycle of the dynamic image thatneeds cycle change, frame image(s) of the determined number are added ordeleted, so that the cycles of the two dynamic images match. Thus, twodynamic images, the cycles of which are equal to one another, namely,two cycle-adjusted data, are generated.

For example, if shorter cycles are adjusted to longer cycles, frameimages are evenly added to the dynamic image having shorter cycles, sothat the cycles of the two dynamic images match. The signal values ofthe pixels of each frame image to be added can be obtained byinterpolation, such as bilinear interpolation or bicubic interpolation,using, for example, signal values of pixels of a plurality of frameimages of the original dynamic image, the pixels being at the samepositions as the pixels of each frame image to be added. On the otherhand, if longer cycles are adjusted to shorter cycles, frame images areevenly thinned out (deleted) from the dynamic image having longercycles, so that the cycles of the two dynamic images match.

Alternatively, as the cycle-adjusted data, the dynamic images havingcycles of temporal change in signal value being equal to one another maybe generated by, in each cycle of the dynamic image(s) that needs cyclechange, selecting a plurality of frame images, and generating aninterpolation image(s) on the basis of the signal values of the selectedframe images and the determined number of frame images. For example, thecycle-adjusted data may be generated by, for each group of correspondingpixels between the frame images of the dynamic image(s) that needs cyclechange, generating a waveform graph showing temporal change in signalvalue and obtaining values at local maximum points and local minimumpoints, and generating an interpolation image(s) by bilinearinterpolation, bicubic interpolation or the like on the basis of thenumber of frame images in each cycle after cycle adjustment and theobtained signal values at the local maximum points and the local minimumpoints, thereby adjusting the number of frame images in each cycle. Thistechnique enables cycle adjustment even if the aboveaddition/thinning-out is not usable (i.e. if frame images cannot beadded/deleted evenly).

After cycle adjustment, shifting amounts in the time direction arecalculated for the respective cycle-adjusted data to match their phasesat the start timing in the two cycle-adjusted data with a predeterminedphase (e.g. a local maximum point or a local minimum point), and theframe images of the cycle-adjusted data are shifted by their respectiveshifting amounts in the time direction. This can match the phases at thestart timing in the two cycle-adjusted data.

Next, the controller 31 calculates, for each pair (or group) of pixelsat the same coordinates on frame images at the same timing (each timing)in the two cycle-adjusted data, a difference value between the signalvalues (e.g. in this embodiment, a value obtained by subtracting thesignal value of the past cycle-adjusted data from the signal value ofthe current cycle-adjusted data) (Step S14), and generates a differenceimage (Step S15).

In Step S15, the controller 31 generates the difference image, forexample, by applying a color for the calculated difference value (a sign(+ or −) and the absolute value) to each pixel of one of the twocycle-adjusted data (e.g. the cycle-adjusted data of the past dynamicimage).

The controller 31 then displays the generated difference image on thedisplay 34 (Step S16) and ends the difference display process A.

FIG. 5 shows an example of the difference image at two different timingsdisplayed in Step S16. As shown in FIG. 5, at the timing when thecurrent signal values are higher than the past signal values, a colorindicating increase in signal value is applied to each pixel with adensity for the magnitude of the absolute value of the difference value.On the other hand, at the timing when the current signal values arelower than the past signal values, a color indicating decrease in signalvalue is applied to each pixel with a density for the magnitude of theabsolute value of the difference value. Hence, a user can readilyunderstand difference between the dynamic images, which are comparedwith one another, in the function to be diagnosed.

Modification from First Embodiment

Although two dynamic images obtained by imaging of the dynamic state ofa subject are compared with one another in the first embodiment, thedifference display process A is also applicable to the case whereanalysis result images are compared with one another, wherein each ofthe analysis result images is obtained by dynamic analysis of a dynamicimage on a pixel-to-pixel basis (i.e. a pixel basis) or on ablock-to-block basis (i.e. a block basis), the block being constitutedof a plurality of pixels (e.g. the case where the controller 31 has afunction to analyze dynamic images and generate analysis result images,and compares an analysis result image obtained by analysis of a currentdynamic image with a past analysis result image of the same patientstored in the storage 32). That is, performing the same processes asthose in Steps S11 to S16 of the difference display process A on twoanalysis result images that are compared with one another visualizesdifference between the images and makes it easy for a user to understandthe difference.

In this modification, warping in Step S11 is performed with the twodynamic images, based on which the two analysis result images have beengenerated. More specifically, warping is performed on the two dynamicimages, based on which the two analysis result images have beengenerated, so as to match the lung field region shapes as describedabove, and the coordinate transform performed on the two dynamic imagesin the warping is also performed on the two analysis result images so asto match the lung field region shapes in the analysis result images.

Each analysis result image is obtained by analysis of a dynamic image ona pixel-to-pixel basis or on a block-to-block basis for the function(ventilation or perfusion) to be diagnosed, the block being constitutedof a plurality of pixels, and the signal value(s) of the pixel(s)thereof is the feature amount relevant to the function to be diagnosed.Although the specific analysis technique for obtaining analysis resultimages is not particularly limited, the (1) to (3) below can be used,for example. In the (1) to (3) below, analysis of a dynamic image isperformed on a block-to-block basis, the block (small region) beingconstituted of a plurality of pixels, but may be performed on apixel-to-pixel basis.

(1) If the function to be diagnosed is perfusion, the techniquedescribed in JP 2012-239796 A can be used, for example. That is, as aperfusion analysis result image, a moving image may be generated bycalculating, for each small region of a series of frame images, a crosscorrelation coefficient of a pulsation signal waveform with a perfusionsignal waveform while shifting the perfusion signal waveform by oneframe interval (in the time direction) with respect to the pulsationsignal waveform obtained from the start of imaging, and arranging imageseach being one frame in which the cross correlation coefficients areshown in the respective small regions, wherein the cross correlationcoefficients for the respective small regions are calculated each timethe perfusion signal waveform is shifted by one frame interval.

The perfusion signal waveform can be obtained by performing high-passfiltering in the time direction (e.g. a lower-limit cutoff frequency of0.8 Hz) on each small region of a series of frame images, calculating arepresentative value (the mean, the maximum, etc.) of the signal valuesof the pixels of each small region, and obtaining a waveform showingtemporal change in the calculated representative value.

As the pulsation signal waveform, any of the following waveforms can beused.

-   -   (a) Waveform that shows temporal change in signal value of ROI        (region of interest) designated in heart region (or main artery        region)    -   (b) Signal waveform obtained by reversing waveform of (a)    -   (c) Cardiac signal waveform obtained from electrocardiographic        sensor    -   (d) Signal waveform that shows motion (change in position) of        heart wall

The cross correlation coefficient can be obtained by the following[Equation 1].

$\begin{matrix}{{c = {\frac{1}{J}{\sum\limits_{j = 1}^{J}\frac{\left\{ {{A(j)} - m_{A}} \right\}\mspace{11mu}\left\{ {{B(j)} - m_{B}} \right\}}{\sigma_{A}\sigma_{B}}}}}{{m_{A} = {\frac{1}{J}{\sum\limits_{j = 1}^{J}{A(j)}}}},{m_{B} = {{\frac{1}{J}{\sum\limits_{j = 1}^{J}{{B(j)}\sigma_{A}}}} = {{\sqrt{\frac{1}{J}{\sum\limits_{j = 1}^{J}\left\{ {{A(j)} - m_{A}} \right\}^{2}}}\sigma_{B}} = \sqrt{\frac{1}{J}{\sum\limits_{j = 1}^{J}\left\{ {{B(j)} - m_{B}} \right\}^{2}}}}}}}} & \left\lbrack {{Equation}\mspace{14mu} 1} \right\rbrack\end{matrix}$

C: Cross correlation coefficient

A(j): Signal value of j^(th) signal of all signals J included inpulsation signal waveform

m_(A): Mean of signal values of all signals included in pulsation signalwaveform

σ_(A): Standard deviation of all signals included in pulsation signalwaveform

B(j): Signal value of j^(th) signal of all signals J included in outputsignal waveform of small region

m_(B): Mean of signal values of all signals included in output signalwaveform of small region

σ_(B): Standard deviation of all signals included in output signalwaveform of small region

(2) If the function to be diagnosed is perfusion, as described in JP2013-81579 A, as a perfusion analysis result image, a moving image maybe generated by performing high-pass filtering in the time direction(e.g. a lower-limit cutoff frequency of 0.8 Hz) on each small region ofa series of frame images, calculating, for each small region, adifference value in representative value (the mean, the maximum, etc.)of the signal values of the pixels between adjacent frame images of eachpossible pair, and arranging images as frames in chronological order,each image being one frame in which the calculated difference valuesbetween the adjacent frame images are shown in the respective smallregions. The inter-frame difference images (constituting the movingimage) generated by the above technique are images from which signalchange due to ventilation in each small region has been removed andwhich show signal change due to perfusion in each small region.

(3) If the function to be diagnosed is ventilation, as described in JP2013-81579 A, as a ventilation analysis result image, a moving image maybe generated by performing low-pass filtering in the time direction(e.g. a higher-limit cutoff frequency of 0.8 Hz) on each small region ofa series of frame images, calculating, for each small region, adifference value in representative value (the mean, the maximum, etc.)of the signal values of the pixels between adjacent frame images of eachpossible pair, and arranging images as frames in chronological order,each image being one frame in which the calculated difference valuesbetween the adjacent frame images are shown in the respective smallregions. The inter-frame difference images (constituting the movingimage) generated by the above technique are images from which signalchange due to perfusion in each small region has been removed and whichshow signal change due to ventilation in each small region.

Second Embodiment

Next, a second embodiment of the invention is described.

The configuration of the second embodiment is the same as that describedin the first embodiment except that, in the second embodiment, a programto perform a difference display process B is stored in the storage 32 ofthe diagnostic console 3. Hence, description of the configuration is notrepeated here, and actions of the second embodiment are describedhereinafter.

First, the imager 1 and the imaging console 2 perform dynamic imaging,thereby generating a dynamic image, and the imaging console 2 sends aseries of frame images of the dynamic image to the diagnostic console 3.

In the diagnostic console 3, when receiving the series of frame imagesof the dynamic image based on which ventilation or perfusion isdiagnosed from the imaging console 2 through the communication unit 35,the controller 31 performs the difference display process B shown inFIG. 6 in corporation with the program stored in the storage 32.

FIG. 6 is a flowchart of the difference display process B that isperformed by the diagnostic console 3 in the second embodiment. Thedifference display process B is performed by the controller 31 incooperation with the program stored in the storage 32.

Hereinafter, the flow of the difference display process B is describedwith reference to FIG. 6.

First, a past dynamic image to be compared with the received dynamicimage is selected (Step S20).

The process in Step S20 is the same as that in Step S10 shown in FIG. 3,and hence description thereof is not repeated here.

Next, the controller 31 calculates the feature amount (here, signalvalue(s) of an ROI) relevant to the function to be diagnosed from eachof the current dynamic image and the past dynamic image, generateswaveform graphs each showing temporal change in the calculated featureamount and obtains cycles thereof (Step S21).

The process in Step 21 is the same as that in Step S12 shown in FIG. 3,and hence description thereof is not repeated here. Note that each dataplotted on each waveform graph is called signal value data.

Next, the controller 31 performs cycle adjustment to match the cycles ofthe waveform graph generated on the basis of the current dynamic imagewith the cycles of the waveform graph generated on the basis of the pastdynamic image, thereby generating two cycle-adjusted data (Step S22).

In Step S22, if the cycles of the waveform graph generated on the basisof the current dynamic image and the cycles of the waveform graphgenerated on the basis of the past dynamic image are different from oneanother as shown in FIG. 4, cycle adjustment is performed, so that theircycles become equal to one another. In this embodiment, thecycle-adjusted data are the waveform graphs, the cycles of which havebeen matched with one another.

For example, first, cycles (cycles of temporal change in signal value;the same applies hereinafter) of the waveform graphs after adjustmentare determined. As the cycles after adjustment, shorter cycles that oneof the dynamic images has may be used so that cycles of the otherdynamic image are adjusted thereto, or longer cycles that one of thedynamic images has may be used so that cycles of the other dynamic imageare adjusted thereto. Alternatively, cycles of both of the dynamicimages may be adjusted to a predetermined cycle(s).

Next, in order to match the cycles of the respective waveform graphswith the cycles after adjustment, for each cycle of each waveform graph,the number of signal value data to be added or deleted is determined. Ifthe number of signal value data to be added or deleted is 0, the cyclesof such a waveform graph are not changed. In each cycle of the waveformgraph that needs cycle change, signal value data of the determinednumber are added or deleted, so that the cycles of the two waveformgraphs match. Thus, two waveform graphs, the cycles of which are equalto one another, namely, two cycle-adjusted data, are generated.

For example, if shorter cycles are adjusted to longer cycles, signalvalue data are evenly added to the waveform graph having shorter cycles,so that the cycles of the two waveform graphs match. The signal valuedata to be added can be obtained by interpolation, such as bilinearinterpolation or bicubic interpolation, using, for example, signal valuedata of the original waveform graph. On the other hand, if longer cyclesare adjusted to shorter cycles, signal value data are evenly thinned out(deleted) from the waveform graph having longer cycles, so that thecycles of the two waveform graphs match. The interval to plot signalvalue data on the waveform graphs is the frame interval in imaging.

Alternatively, a waveform graph(s) having cycles that are the determinedcycles may be newly generated by, in each cycle of the waveform graph(s)that needs cycle change, selecting a plurality of signal value data(e.g. a local maximum point and a local minimum point), and performinginterpolation on the basis of the selected signal value data and thecycles of the waveform graphs after adjustment. For example, thecycle-adjusted data may be generated by, from the waveform graph(s) thatneeds cycle change, obtaining local maximum points and local minimumpoints of signal value data, and interpolating signal value data bybilinear interpolation, bicubic interpolation or the like on the basisof the cycles after adjustment and the signal value data of the obtainedlocal maximum points and local minimum points, thereby adjusting thecycles of the waveform graph(s). This technique enables cycle adjustmenteven if the above addition/thinning-out is not usable (i.e. if signalvalue data cannot be added/deleted evenly).

After cycle adjustment, shifting amounts in the time direction arecalculated for the respective cycle-adjusted data to match their phasesat the start timing in the two cycle-adjusted data with a predeterminedphase (e.g. a local maximum point or a local minimum point), and thesignal value data of the cycle-adjusted data are shifted by theirrespective shifting amounts in the time direction. This can match thephases at the start timing in the two cycle-adjusted data.

Next, the controller 31 calculates difference values between the signalvalues at the respective same timings in the two cycle-adjusted data(e.g. values obtained by subtracting the signal value data of thecycle-adjusted data of the waveform graph generated on the basis of thepast dynamic image (past cycle-adjusted data) from their correspondingsignal value data of the cycle-adjusted data of the waveform graphgenerated on the basis of the current dynamic image (currentcycle-adjusted data)) (Step S23), and generates a difference graph (StepS24).

In Step S24, the controller 31 generates the difference graph, forexample, by integrating the two cycle-adjusted data (graphs) into one,adding a waveform of the difference values onto the graph, and applyingcolors for the difference values to the waveform of the differencevalues.

The controller 31 then displays the generated difference graph on thedisplay 34 (Step S25) and ends the difference display process B.

FIG. 7 shows an example of the difference graph displayed in Step S25.As shown in FIG. 7, in the difference graph, the waveforms showingtemporal change in the feature amount in the two dynamic images, namely,the past dynamic image and the current dynamic image, and the waveformshowing difference therebetween are superimposed and displayed. At thetimings when the current signal values are higher than the past signalvalues, a color indicating increase in signal value is applied to thewaveform showing the difference. On the other hand, at the timings whenthe current signal values are lower than the past signal values, a colorindicating decrease in signal value is applied to the waveform showingthe difference. Hence, a user can readily understand difference betweenthe dynamic images, which are compared with one another, in the functionto be diagnosed.

Modification from Second Embodiment

Although two dynamic images obtained by imaging of the dynamic state ofa subject are compared with one another in the second embodiment, thedifference display process B is also applicable to the case whereanalysis result images are compared with one another, wherein each ofthe analysis result images is obtained by dynamic analysis of a dynamicimage on a pixel-to-pixel basis or on a block-to-block basis, the blockbeing constituted of a plurality of pixels (e.g. the case where thecontroller 31 has a function to analyze dynamic images and generateanalysis result images, and compares an analysis result image obtainedby analysis of a current dynamic image with a past analysis result imageof the same patient stored in the storage 32). That is, performing thesame processes as those in Steps S21 to S25 of the difference displayprocess B on two analysis result images that are compared with oneanother visualizes difference between the images and makes it easy for auser to understand the difference.

Examples of the analysis result images are the same as those describedin the first embodiment. Hence, description thereof is not repeatedhere.

Third Embodiment

Next, a third embodiment of the invention is described.

The configuration of the third embodiment is the same as that describedin the first embodiment except that, in the third embodiment, a programto perform a difference display process C is stored in the storage 32 ofthe diagnostic console 3. Hence, description of the configuration is notrepeated here, and actions of the third embodiment are describedhereinafter.

First, the imager 1 and the imaging console 2 perform dynamic imaging,thereby generating a dynamic image, and the imaging console 2 sends aseries of frame images of the dynamic image to the diagnostic console 3.

In the diagnostic console 3, when receiving the series of frame imagesof the dynamic image based on which the function of the diaphragm isdiagnosed from the imaging console 2 through the communication unit 35,the controller 31 performs the difference display process C shown inFIG. 8 in corporation with the program stored in the storage 32.

FIG. 8 is a flowchart of the difference display process C that isperformed by the diagnostic console 3 in the third embodiment. Thedifference display process C is performed by the controller 31 incooperation with the program stored in the storage 32.

Hereinafter, the flow of the difference display process C is describedwith reference to FIG. 8.

First, a past dynamic image to be compared with the received dynamicimage is selected (Step S30).

The process in Step S30 is the same as that in Step S10 shown in FIG. 3,and hence description thereof is not repeated here.

Next, the controller 31 performs warping on the current dynamic imageand the past dynamic image so as to perform position adjustment of theclavicle or the thorax (Step S31).

For example, in Step S31, first, the clavicle or the thorax is extractedin each frame image of the current dynamic image and each frame image ofthe past dynamic image. The clavicle or the thorax can be extracted, forexample, by template matching on each frame image using a preparedtemplate, such as a clavicle template, a rib template or a sternumtemperate, or by application of curve fitting function to each frameimage after edge detection. Further, on the basis of features, such asthe position, shape, size, concentration gradient and direction, basedon previous knowledge of bone structures of the clavicle and/or thethorax, whether or not the extracted region(s) is the clavicle or thethorax may be carefully examined so that excessively extracted parts canbe distinguished and removed. Next, one frame image is selected from allthe frame images of the current dynamic image and the past dynamic imageas a reference image, and warping is performed such that the position ofthe clavicle or the thorax in the other frame images matches theposition of the clavicle or the thorax in the reference image. Thereference image may be the first frame image of the current dynamicimage or the past dynamic image, or may be a frame image at the maximalexpiratory level or the maximal inspiratory level.

Next, the controller 31 calculates the feature amount (here, theposition of the diaphragm (i.e. the diaphragm position)) relevant to thefunction to be diagnosed from each of the current dynamic image and thepast dynamic image, and obtains cycles of temporal change in thecalculated feature amount (Step S32).

In Step S32, first, the diaphragm position in each frame image of thecurrent dynamic image and the past dynamic image is identified. In aplain chest roentgenogram taken from the front, the diaphragm appears tobe in contact with the bottom of the lung fields. Hence, for example,the lung field regions are extracted in each frame image, and thecontours at the bottom of the extracted lung field regions can beidentified as the diaphragm position.

Next, for each of the current dynamic image and the past dynamic image,a representative value (e.g. the mean, the median, etc.) of ycoordinates of the diaphragm position identified in each frame image iscalculated, and a graph of the waveform (called a waveform graph)showing temporal change in diaphragm position is generated by plottingthe calculated representative values in chronological order (in order ofthe frame images). The horizontal direction and the vertical directionof each image are the x direction and the y direction, respectively. Inaddition, the upper left of each image is the origin, and the ycoordinate value is larger on the lower side in the y direction.

Then, cycles of temporal change in diaphragm position in the currentdynamic image and the past dynamic image are obtained from therespective waveform graphs generated. Time from a local maximum point(or local minimum point) to the next local maximum point (or localminimum point) of the waveform graph(s) showing temporal change indiaphragm position can be calculated as a cycle.

Next, the controller 31 performs cycle adjustment to match the cyclesobtained from the current dynamic image with the cycles obtained fromthe past dynamic image, thereby generating two cycle-adjusted data (StepS33).

In Step S33, if the cycles obtained from the current dynamic image andthe cycles obtained from the past dynamic image are different from oneanother as shown in FIG. 4, cycle adjustment is performed, so that twocycle-adjusted data, the cycles of which are equal to one another, aregenerated. In this embodiment, cycle-adjusted data are the dynamicimages, the cycles of which have been matched with one another (here,the current dynamic image and the past dynamic image, the cycles ofwhich have been matched with one another).

For example, first, cycles (cycles of temporal change in diaphragmposition; the same applies hereinafter) of the dynamic images afteradjustment are determined. As the cycles after adjustment, shortercycles that one of the dynamic images has may be used so that cycles ofthe other dynamic image are adjusted thereto, or longer cycles that oneof the dynamic images has may be used so that cycles of the otherdynamic image are adjusted thereto. Alternatively, cycles of both of thedynamic images may be adjusted to a predetermined cycle(s).

Next, in order to match the cycles of the respective dynamic images withthe cycles after adjustment, for each cycle of each dynamic image, thenumber of frame images to be added or deleted is determined. If thenumber of frame images to be added or deleted is 0, the cycles of such adynamic image are not changed. In each cycle of the dynamic image thatneeds cycle change, frame image(s) of the determined number are added ordeleted, so that cycles of the two dynamic images match. Thus, twodynamic images, the cycles of which are equal to one another, namely,two cycle-adjusted data, are generated.

For example, if shorter cycles are adjusted to longer cycles, frameimages are evenly added to the dynamic image having shorter cycles, sothat the cycles of the two dynamic images match. The signal values ofthe pixels of each frame image to be added can be obtained byinterpolation, such as bilinear interpolation or bicubic interpolation,using, for example, signal values of a plurality of frame images of theoriginal dynamic image. On the other hand, if longer cycles are adjustedto shorter cycles, frame images are evenly thinned out (deleted) fromthe dynamic image having longer cycles, so that the cycles of the twodynamic images match.

Alternatively, as the cycle-adjusted data, the dynamic images havingcycles of temporal change in diaphragm position being equal to oneanother may be generated by, in each cycle of the dynamic image(s) thatneeds cycle change, selecting a plurality of frame images (e.g. imagescorresponding to a local maximum point and a local minimum point of thewaveform graph(s) showing temporal change in the diaphragm position),and generating an interpolation image(s) by interpolation, such asbilinear interpolation or bicubic interpolation, on the basis of theselected frame images and the determined number of frame images. Thistechnique enables cycle adjustment even if the aboveaddition/thinning-out is not usable (i.e. if frame images cannot beadded/deleted evenly).

After cycle adjustment, shifting amounts in the time direction arecalculated for the respective cycle-adjusted data to match their phasesat the start timing in the two cycle-adjusted data with a predeterminedphase (e.g. a local maximum point or a local minimum point) of temporalchange in diaphragm position, and the signal values of thecycle-adjusted data are shifted by their respective shifting amounts inthe time direction. This can match the phases at the start timing in thetwo cycle-adjusted data.

Next, the controller 31 calculates difference values in the diaphragmposition between frame images at the respective same timings in the twocycle-adjusted data (Step S34). More specifically, the controller 31calculates a difference value in the vertical direction between thediaphragm position in each frame image of the current cycle-adjusteddata and the diaphragm position in each frame image of the pastcycle-adjusted data, the frame images being at the same timing.

Next, the controller 31 generates, on the basis of the obtaineddifference information, a difference image in which the differenceinformation is superimposed on each frame image of one of the twocycle-adjusted data (Step S35).

In Step S35, the controller 31 generates the difference image, forexample, by applying different colors to the current diaphragm position,the past diaphragm position and a region therebetween (differenceregion) in each frame image of one of the two cycle-adjusted data (e.g.the cycle-adjusted data of the past dynamic image). To the differenceregion, a color for a sign (+ or −) of the difference value is applied,for example.

The controller 31 then displays the generated difference image on thedisplay 34 (Step S36) and ends the difference display process C.

FIG. 9 shows an example of the difference image displayed in Step S36.As shown in FIG. 9, at the timing when the current diaphragm position ishigher than the past diaphragm position (the difference value ispositive (+)), a color indicating that the current diaphragm position ishigher than the past diaphragm position is applied to the differenceregion between the current diaphragm position and the past diaphragmposition. On the other hand, at the timing when the current diaphragmposition is lower than the past diaphragm position (the difference valueis negative (−)), a color indicating that the current diaphragm positionis lower than the past diaphragm position is applied to the differenceregion between the current diaphragm position and the past diaphragmposition. Hence, a user can readily understand difference between thedynamic images, which are compared with one another.

In the above, the first to third embodiments are described. However, thematters described in the above embodiments are some of preferredexamples of the invention, and not intended to limit the invention.

For example, although the phases of the two cycle-adjusted data at thestart timing are adjusted by shifting at least one of the cycle-adjusteddata in the time direction in relation to one another in the above firstembodiment and modification therefrom, this phase adjustment on the twocycle-adjusted data may be performed on a pixel-to-pixel basis. Forexample, as to perfusion in the lung fields, there may be phase lagbetween phases of temporal change in signal value near the heart andphases of temporal change in signal value at the distil end. If thephases about all the pixels of at least one of the cycle-adjusted dataare uniformly shifted as described in the above first embodiment andmodification therefrom, the phase lag due to the positions of the pixelsremains, so that a user can understand the phase lag due to thepositions of the pixels of the dynamic image(s) (analysis resultimage(s)). On the other hand, if shifting amounts in the time directionare determined for the respective pixels of the two cycle-adjusted data,the pixels of one cycle-adjusted data respectively corresponding to thepixels of the other cycle-adjusted data, and phase adjustment isperformed such that phases about all the pixels are matched with oneanother, a user can readily judge difference in the magnitude of thedifference value at each phase due to the positions of the pixels.

Further, if the type of the function to be diagnosed is the function ofthe diaphragm, a difference graph of waveform graphs showing temporalchange in diaphragm position in two dynamic images that are comparedwith one another may be generated and displayed on the display 34. Thedifference graph of the waveform graphs of the diaphragm position can begenerated by calculating the waveform graphs of the diaphragm positionin Step S21 of the difference display process B shown in FIG. 6 usingthe technique described in Step S32 in FIG. 8, and performing the sameprocesses as those in Steps S22 to S24 on the generated waveform graphs.In these steps, the “cycles” are replaced by the “cycles of temporalchange in diaphragm position”, and the “signal value data” are replacedby “diaphragm position data”. The diaphragm position data each indicatesdata of the value of the diaphragm position plotted on each waveformgraph of the diaphragm position.

Further, in the above embodiments, cycle-adjusted data based on twodynamic images or two analysis result images that are compared with oneanother are generated. However, the number of dynamic images or analysisresult images that are compared with one another is not limited to twoand may be more than two.

Further, although the display 34 is used as an output device in theabove embodiments, another output device, such as a printer, may beused.

Further, although generation of the difference information (differenceimage or difference graph) from the dynamic images or the analysisresult images and display of the generated difference information areboth performed by a single apparatus in the above embodiments, theseprocesses may be performed by different apparatuses. For example,generation of the difference information (difference image or differencegraph) from the dynamic images or the analysis result images may beperformed by an apparatus, and display of the generated differenceinformation may be performed by another apparatus.

Further, in the above embodiments, the difference image is generated inthe first embodiment and the third embodiments, and the difference graphis generated in the second embodiment. However, the diagnostic console 3may have a function to generate both of the difference image and thedifference graph, and be configured such that a user can choose one ofthem to be generated and displayed with the operation unit 33.

Further, for example, in the above, as a computer readable medium forthe programs of the invention, a hard disk, a nonvolatile semiconductormemory or the like is used. However, the computer readable medium is notlimited thereto, and may be a portable recording/storage medium, such asa CD-ROM. Further, as a medium to provide data of the programs of theinvention, a carrier wave can be used.

In addition to the above, the specific configurations/components and thespecific actions of the apparatuses of the dynamic analysis system canalso be appropriately modified without departing from the spirit of theinvention.

Although embodiments of the invention have been described andillustrated in detail, the disclosed embodiments are made for purposesof illustration and example only and not limitation. The scope of theinvention should be interpreted by terms of the appended claims.

The entire disclosure of Japanese Patent Application No. 2017-045532filed on Mar. 10, 2017 is incorporated herein by reference in itsentirety.

What is claimed is:
 1. A dynamic analysis system comprising: a hardwareprocessor that: obtains a cycle of temporal change in a feature amountrelevant to a function to be diagnosed from each of dynamic imagesobtained by imaging of a dynamic state of a living body with radiation;adjusts the obtained cycle, thereby generating a plurality ofcycle-adjusted data having cycles of the temporal change in the featureamount being equal to one another; and generates difference informationat each phase in the plurality of cycle-adjusted data; and an outputdevice that outputs the difference information.
 2. The dynamic analysissystem according to claim 1, wherein the hardware processor adds ordeletes a frame image to or from at least one of the dynamic images soas to adjust a number of frame images in the cycle of the temporalchange in the feature amount, thereby generating dynamic images havingcycles of the temporal change in the feature amount being equal to oneanother as the plurality of cycle-adjusted data.
 3. The dynamic analysissystem according to claim 2, wherein the hardware processor calculatessignal values of pixels of the frame image to be added to the at leastone of the dynamic images by interpolation using signal values of aplurality of frame images of the at least one of the dynamic images. 4.The dynamic analysis system according to claim 2, wherein the hardwareprocessor: generates the plurality of cycle-adjusted data having phasesat a start timing being matched with one another; and calculates adifference value between signal values of pixels at same coordinates onframe images at a same timing in the plurality of cycle-adjusted data.5. The dynamic analysis system according to claim 4, wherein the dynamicimages are dynamic chest images, and the hardware processor matches lungfield region shapes in the dynamic images with one another.
 6. Thedynamic analysis system according to claim 5, wherein the hardwareprocessor transforms the lung field region shapes in the dynamic imagesto a predetermined lung field region shape.
 7. The dynamic analysissystem according to claim 2, wherein the dynamic images are dynamicchest images, and the hardware processor: obtains the cycle of thetemporal change in a diaphragm position as the feature amount from eachof the dynamic images; adjusts the cycle and the phase of the temporalchange in the diaphragm position, thereby generating the plurality ofcycle-adjusted data having the cycles of the temporal change in thediaphragm position being equal to one another and phases at a starttiming being matched with one another; and generates the differenceinformation on the diaphragm position in frame images at a same timingin the plurality of cycle-adjusted data.
 8. The dynamic analysis systemaccording to claim 1, wherein the hardware processor generates aninterpolation image for at least one of the dynamic images based onsignal values of a plurality of frame images selected from frame imagesof the at least one of the dynamic images so as to adjust a number offrame images in the cycle of the temporal change in the feature amount,thereby generating dynamic images having cycles of the temporal changein the feature amount being equal to one another as the plurality ofcycle-adjusted data.
 9. The dynamic analysis system according to claim1, wherein the hardware processor: generates graphs showing the temporalchange in the feature amount relevant to the function to be diagnosedfrom the respective dynamic images; obtains the cycle of the temporalchange in the feature amount based on each of the generated graphs; andchanges the cycle of at least one of the graphs showing the temporalchange in the feature amount generated from the respective dynamicimages, thereby generating graphs having cycles of the temporal changein the feature amount being equal to one another.
 10. The dynamicanalysis system according to claim 9, wherein the hardware processor:generates the plurality of cycle-adjusted data having phases at a starttiming being matched with one another; and calculates a difference valuein the feature amount at a same timing in the plurality ofcycle-adjusted data.
 11. The dynamic analysis system according to claim1, wherein the hardware processor combines the difference informationwith at least one of the plurality of cycle-adjusted data, and causesthe output device to output the difference information combined with theat least one of the plurality of cycle-adjusted data.
 12. The dynamicanalysis system according to claim 1, wherein the dynamic images aredynamic chest images, the function to be diagnosed is a perfusionfunction or a ventilation function in a lung field, and the featureamount is a signal value of a pixel in a region of interest.
 13. Thedynamic analysis system according to claim 1, wherein the dynamic imagesare dynamic chest images, the function to be diagnosed is a function ofa diaphragm, and the feature amount is a diaphragm position.
 14. Adynamic analysis system comprising: a hardware processor that: obtains acycle of temporal change in a feature amount relevant to a function tobe diagnosed from each of analysis result images of respective dynamicimages obtained by imaging of a dynamic state of a living body withradiation, wherein the analysis result images show results of dynamicanalysis of the respective dynamic images on a pixel basis or a blockbasis, the block being constituted of a plurality of pixels; adjusts theobtained cycle, thereby generating a plurality of cycle-adjusted datahaving cycles of the temporal change in the feature amount being equalto one another; and generates difference information at each phase inthe plurality of cycle-adjusted data; and an output device that outputsthe difference information.
 15. The dynamic analysis system according toclaim 14, wherein the hardware processor adds or deletes a frame imageto or from at least one of the analysis result images so as to adjust anumber of frame images in the cycle of the temporal change in thefeature amount, thereby generating analysis result images having cyclesof the temporal change in the feature amount being equal to one anotheras the plurality of cycle-adjusted data.
 16. The dynamic analysis systemaccording to claim 15, wherein the hardware processor calculates signalvalues of pixels of the frame image to be added to the at least one ofthe analysis result images by interpolation using signal values ofpixels of a plurality of frame images of the at least one of theanalysis result images, the pixels being at same positions as the pixelsof the frame image to be added.
 17. The dynamic analysis systemaccording to claim 15, wherein the hardware processor: generates theplurality of cycle-adjusted data having phases at a start timing beingmatched with one another; and calculates a difference value betweensignal values of pixels at same coordinates on frame images at a sametiming in the plurality of cycle-adjusted data.
 18. The dynamic analysissystem according to claim 14, wherein the hardware processor generatesan interpolation image for at least one of the analysis result imagesbased on signal values of a plurality of frame images selected fromframe images of the at least one of the analysis result images so as toadjust a number of frame images in the cycle of the temporal change inthe feature amount, thereby generating analysis result images havingcycles of the temporal change in the feature amount being equal to oneanother as the plurality of cycle-adjusted data.
 19. The dynamicanalysis system according to claim 14, wherein the hardware processor:generates graphs showing the temporal change in the feature amountrelevant to the function to be diagnosed from the respective analysisresult images; obtains the cycle of the temporal change in the featureamount based on each of the generated graphs; and changes the cycle ofat least one of the graphs showing the temporal change in the featureamount generated from the respective analysis result images, therebygenerating graphs having cycles of the temporal change in the featureamount being equal to one another.
 20. The dynamic analysis systemaccording to claim 19, wherein the hardware processor: generates theplurality of cycle-adjusted data having phases at a start timing beingmatched with one another; and calculates a difference value betweensignal values at a same timing in the plurality of cycle-adjusted data.21. The dynamic analysis system according to claim 14, wherein thehardware processor combines the difference information with at least oneof the plurality of cycle-adjusted data, and causes the output device tooutput the difference information combined with the at least one of theplurality of cycle-adjusted data.
 22. The dynamic analysis systemaccording to claim 14, wherein the dynamic images are dynamic chestimages, the function to be diagnosed is a perfusion function or aventilation function in a lung field, and the feature amount is a signalvalue of a pixel in a region of interest.
 23. The dynamic analysissystem according to claim 14, wherein the dynamic images are dynamicchest images, the function to be diagnosed is a function of a diaphragm,and the feature amount is a diaphragm position.